NASA - FIRMS fire spread around Nowra

Summary

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Packages

library(tidyverse)

## ── Attaching packages ───────────────────────── tidyverse 1.3.0 ──

## ✓ ggplot2 3.2.1     ✓ purrr   0.3.3
## ✓ tibble  2.1.3     ✓ dplyr   0.8.3
## ✓ tidyr   1.0.0     ✓ stringr 1.4.0
## ✓ readr   1.3.1     ✓ forcats 0.4.0

## ── Conflicts ──────────────────────────── tidyverse_conflicts() ──
## x dplyr::filter() masks stats::filter()
## x dplyr::lag()    masks stats::lag()

library(ggmap)

## Google's Terms of Service: https://cloud.google.com/maps-platform/terms/.

## Please cite ggmap if you use it! See citation("ggmap") for details.

library(lubridate)

## 
## Attaching package: 'lubridate'

## The following object is masked from 'package:base':
## 
##     date

library(gganimate)

Loading data

raw = readr::read_csv("DL_FIRE_M6_94689/fire_nrt_M6_94689.csv")

## Parsed with column specification:
## cols(
##   latitude = col_double(),
##   longitude = col_double(),
##   brightness = col_double(),
##   scan = col_double(),
##   track = col_double(),
##   acq_date = col_date(format = ""),
##   acq_time = col_character(),
##   satellite = col_character(),
##   instrument = col_character(),
##   confidence = col_double(),
##   version = col_character(),
##   bright_t31 = col_double(),
##   frp = col_double(),
##   daynight = col_character()
## )

glimpse(raw)

## Observations: 101,639
## Variables: 14
## $ latitude   <dbl> -35.493, -33.992, -33.991, -33.985, -33.983, -33.980, -33.…
## $ longitude  <dbl> 149.639, 150.129, 150.118, 150.085, 150.074, 150.051, 150.…
## $ brightness <dbl> 379.8, 380.4, 406.0, 334.4, 335.3, 329.2, 330.7, 327.1, 34…
## $ scan       <dbl> 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.1, 1.0, 1.0, 1.0, 1.0…
## $ track      <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1…
## $ acq_date   <date> 2019-12-01, 2019-12-01, 2019-12-01, 2019-12-01, 2019-12-0…
## $ acq_time   <chr> "0000", "0000", "0000", "0000", "0000", "0000", "0000", "0…
## $ satellite  <chr> "Terra", "Terra", "Terra", "Terra", "Terra", "Terra", "Ter…
## $ instrument <chr> "MODIS", "MODIS", "MODIS", "MODIS", "MODIS", "MODIS", "MOD…
## $ confidence <dbl> 94, 100, 100, 66, 67, 70, 75, 59, 94, 100, 86, 80, 51, 46,…
## $ version    <chr> "6.0NRT", "6.0NRT", "6.0NRT", "6.0NRT", "6.0NRT", "6.0NRT"…
## $ bright_t31 <dbl> 288.9, 305.2, 315.7, 299.8, 299.1, 298.9, 299.0, 298.1, 29…
## $ frp        <dbl> 156.0, 157.8, 300.1, 28.2, 30.0, 24.0, 26.1, 21.4, 55.2, 1…
## $ daynight   <chr> "D", "D", "D", "D", "D", "D", "D", "D", "D", "D", "D", "D"…

raw$acq_time %>% unique %>% sample(size = 50) ## Four digits time stamp

##  [1] "0700" "1305" "2345" "1635" "0545" "0455" "0640" "0605" "0450" "0015"
## [11] "1325" "0445" "0500" "1245" "0105" "2340" "1415" "0635" "0155" "1655"
## [21] "1650" "0540" "1730" "1350" "1420" "0440" "0020" "1615" "1155" "0530"
## [31] "0320" "1620" "1425" "1300" "0125" "1735" "0555" "0300" "1545" "1725"
## [41] "1335" "0315" "0505" "0355" "1750" "1610" "0430" "0405" "0225" "1755"

Basic data cleaning and variable selection

I am only selecting some variables of interest to me.

clean = raw %>% 
  dplyr::transmute(
    latitude,
    longitude,
    brightness,
    confidence,
    bright_t31,
    frp,
    daynight,
    my_time = paste0(acq_date, " ", acq_time) %>% 
      lubridate::ymd_hm(), ## Aftering pasting the hours and minites, we use lubridate to clean this 
    confidence,
    conf_cat = cut(
      confidence, 
      c(-1, 50, 101), 
      labels = c("low", "high")) %>% as.factor,
    brightness,
    bright_cat = cut(
      brightness, 
      c(300, 350, 400, Inf), 
      labels = c("low", "med", "high")) %>% as.factor
  )

glimpse(clean)

## Observations: 101,639
## Variables: 10
## $ latitude   <dbl> -35.493, -33.992, -33.991, -33.985, -33.983, -33.980, -33.…
## $ longitude  <dbl> 149.639, 150.129, 150.118, 150.085, 150.074, 150.051, 150.…
## $ brightness <dbl> 379.8, 380.4, 406.0, 334.4, 335.3, 329.2, 330.7, 327.1, 34…
## $ confidence <dbl> 94, 100, 100, 66, 67, 70, 75, 59, 94, 100, 86, 80, 51, 46,…
## $ bright_t31 <dbl> 288.9, 305.2, 315.7, 299.8, 299.1, 298.9, 299.0, 298.1, 29…
## $ frp        <dbl> 156.0, 157.8, 300.1, 28.2, 30.0, 24.0, 26.1, 21.4, 55.2, 1…
## $ daynight   <chr> "D", "D", "D", "D", "D", "D", "D", "D", "D", "D", "D", "D"…
## $ my_time    <dttm> 2019-12-01, 2019-12-01, 2019-12-01, 2019-12-01, 2019-12-0…
## $ conf_cat   <fct> high, high, high, high, high, high, high, high, high, high…
## $ bright_cat <fct> med, med, high, low, low, low, low, low, low, med, low, lo…

Google Maps

This code is not reproducible unless you have the correct Google Maps API.

nowra_map <- get_map("Nowra Hill, NSW", zoom = 10)

## Source : https://maps.googleapis.com/maps/api/staticmap?center=Nowra%20Hill,%20NSW&zoom=10&size=640x640&scale=2&maptype=terrain&language=en-EN&key=xxx

## Source : https://maps.googleapis.com/maps/api/geocode/json?address=Nowra+Hill,+NSW&key=xxx

str(nowra_map)

##  'ggmap' chr [1:1280, 1:1280] "#BABAB6" "#D6D6CA" "#EAEADE" "#EAEAE2" ...
##  - attr(*, "source")= chr "google"
##  - attr(*, "maptype")= chr "terrain"
##  - attr(*, "zoom")= num 10
##  - attr(*, "bb")=Classes 'tbl_df', 'tbl' and 'data.frame':   1 obs. of  4 variables:
##   ..$ ll.lat: num -35.3
##   ..$ ll.lon: num 150
##   ..$ ur.lat: num -34.6
##   ..$ ur.lon: num 151

map_bounds = attr(nowra_map, "bb")

Subsetting the fire data to only those in the map

nowra_data = clean %>% 
  dplyr::filter(
    latitude >= map_bounds$ll.lat,
    latitude <= map_bounds$ur.lat,
    longitude >= map_bounds$ll.lon,
    longitude <= map_bounds$ur.lon)

nowra_data %>% glimpse

## Observations: 2,137
## Variables: 10
## $ latitude   <dbl> -35.285, -35.284, -35.290, -35.286, -34.964, -34.963, -34.…
## $ longitude  <dbl> 150.246, 150.235, 150.171, 150.209, 150.639, 150.627, 150.…
## $ brightness <dbl> 326.3, 335.0, 337.7, 314.1, 323.6, 311.1, 311.6, 319.1, 33…
## $ confidence <dbl> 43, 83, 100, 50, 100, 82, 83, 98, 76, 70, 63, 100, 100, 10…
## $ bright_t31 <dbl> 296.4, 295.3, 290.2, 288.5, 287.4, 285.9, 286.7, 287.0, 30…
## $ frp        <dbl> 20.0, 31.8, 44.5, 14.1, 28.1, 15.1, 14.7, 22.3, 95.0, 7.3,…
## $ daynight   <chr> "D", "D", "N", "N", "N", "N", "N", "N", "D", "N", "N", "N"…
## $ my_time    <dttm> 2019-12-17 00:00:00, 2019-12-17 00:00:00, 2019-12-17 15:1…
## $ conf_cat   <fct> low, high, high, low, high, high, high, high, high, high, …
## $ bright_cat <fct> low, low, low, low, low, low, low, low, low, low, low, med…

p1 = ggmap(nowra_map) +
  geom_point(data = nowra_data, 
             aes(x = longitude,
                 y = latitude,
                 colour = brightness)) +
  geom_point(x = 150.5934431,
             y = -34.8432388,
             colour = "blue", size = 2) + ## A location near my home
  scale_colour_distiller(palette = "Reds", direction = 1) +
  transition_states(my_time) +
  labs(title = "Time: {closest_state}") +
    shadow_trail(distance = 0.05, colour = "black", alpha = 1)

p2 = animate(p1, nframes = 100, fps = 3)

p2

sessionInfo()

## R version 3.6.1 (2019-07-05)
## Platform: x86_64-apple-darwin15.6.0 (64-bit)
## Running under: macOS Mojave 10.14.6
## 
## Matrix products: default
## BLAS:   /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRblas.0.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRlapack.dylib
## 
## locale:
## [1] en_AU.UTF-8/en_AU.UTF-8/en_AU.UTF-8/C/en_AU.UTF-8/en_AU.UTF-8
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
## 
## other attached packages:
##  [1] gganimate_1.0.4 lubridate_1.7.4 ggmap_3.0.0     forcats_0.4.0  
##  [5] stringr_1.4.0   dplyr_0.8.3     purrr_0.3.3     readr_1.3.1    
##  [9] tidyr_1.0.0     tibble_2.1.3    ggplot2_3.2.1   tidyverse_1.3.0
## 
## loaded via a namespace (and not attached):
##  [1] Rcpp_1.0.3         lattice_0.20-38    prettyunits_1.0.2  png_0.1-7         
##  [5] utf8_1.1.4         assertthat_0.2.1   zeallot_0.1.0      digest_0.6.23     
##  [9] R6_2.4.1           cellranger_1.1.0   plyr_1.8.5         backports_1.1.5   
## [13] reprex_0.3.0       evaluate_0.14      httr_1.4.1         pillar_1.4.2      
## [17] RgoogleMaps_1.4.4  rlang_0.4.2        progress_1.2.2     curl_4.3          
## [21] lazyeval_0.2.2     readxl_1.3.1       gifski_0.8.6       rstudioapi_0.10   
## [25] rmarkdown_2.0      labeling_0.3       munsell_0.5.0      broom_0.5.2       
## [29] compiler_3.6.1     modelr_0.1.5       xfun_0.11          pkgconfig_2.0.3   
## [33] base64enc_0.1-3    htmltools_0.4.0    tidyselect_0.2.5   fansi_0.4.0       
## [37] crayon_1.3.4       dbplyr_1.4.2       withr_2.1.2        bitops_1.0-6      
## [41] grid_3.6.1         nlme_3.1-142       jsonlite_1.6       gtable_0.3.0      
## [45] lifecycle_0.1.0    DBI_1.0.0          magrittr_1.5       scales_1.1.0      
## [49] cli_2.0.0          stringi_1.4.3      farver_2.0.1       fs_1.3.1          
## [53] xml2_1.2.2         generics_0.0.2     vctrs_0.2.0        RColorBrewer_1.1-2
## [57] rjson_0.2.20       tools_3.6.1        glue_1.3.1         tweenr_1.0.1      
## [61] hms_0.5.2          jpeg_0.1-8.1       yaml_2.2.0         colorspace_1.4-1  
## [65] rvest_0.3.5        knitr_1.26         haven_2.2.0